Online retailers like to keep their clients engaged, and who wouldn’t like to have clients in their stores all the time! In that effort, retailers like to keep a much more personalized approach with what is shown depending on what they’ve recently browsed for, what they’ve purchased in the past, what reviews they have submitted and for which product have they up-voted other customer’s reviews. These are a part of the personalizing a customer’s shopping experience so they keep buying what you sell. Today we’re going to discuss about various ways to personalize online shopping experience. So, if you’re an online retailer, then these eCommerce site personalization tips are for you.
Historic Data
Keep an eye on your customer’s past experience for purchases they’ve made and what reviews they posted. Any kind of email interactions that took place could probably hint on their possible future purchases. Check to see if they’re a member of your loyalty program or if they’ve gained enough points that could qualify them for a free purchase of any product they may have shown interest in.
Browsing Behavior
Using various online tools there are ways to study customer behavior on your website and what products they have been browsing, which ones ended in the cart but not brought, what are the items on their wish list and what could be the best time to show deals for it and what items were removed from the cart. These data points could help predict what a user may look for on their future visits and maybe even showcase abandoned cart items on discount to attract the customer. Customers usually see a footer with options showing products that other customers have brought. There is a good chance a customer who brought a shoe recently, might be looking for a nice pair of socks too.
eCommerce Personalization Device Track – Data capture could help personalizing customer experience with data points like:
- Types of Devices used
- Day and time
- Sex and age group
- Income
- Page landing referral source
- First time visitor vs. registered members
- Geo-location
- Average time spent on each page
- Adding items to cart
- Purchase history
- Order value
- View rate vs. purchase rate and more.
Retailers who keep track of a user’s browsing behavior from device to device including the above-mentioned data points could help predict of when a customer is most likely to buy. Customer’s every visit to the online store provides information for a possible sale if products are curated accordingly, maybe even by offering a discount or free shipping.
Region based discount also works well If you’re a retailer who sells in a few countries and discounts could be applied region based. For example, if a customer is browsing a shirt or a shoe in the US store and travels to UK in the meantime, a pop up showing up with a projected discount could be shown to draw their attention with a possible discount, a price change based on region, free shipping (since the store is UK based) and maybe even a freebie to go with it might attract them to make a purchase.
